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Colorectal cancer (CRC) grading is typically carried out by assessing the degree of gland formation within histology images.
Computer-aided classification of breast cancer nuclei
F Schnorrenberg, CS Pattichis, CN Schizas, K Kyriacou, and M Vassiliou · 1996
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The farthest point strategy for progressive image sampling
Yuval Eldar, Michael Lindenbaum, Moshe Porat, and Yehoshua Y Zeevi · 1997
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Computer-assisted differential diagnosis of malignant mesothelioma based on syntactic structure analysis
Barbara Weyn, Gert van de Wouwer, Samir Kumar-Singh, André van Daele, Paul Scheunders, Eric Van Marck, and Willem Jacob · 1999
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Prognostic factors in colorectal cancer: College of american pathologists consensus statement 1999
Carolyn C Compton, L Peter Fielding, Lawrence J Burgart, Barbara Conley, Harry S Cooper, Stanley R Hamilton, M Elizabeth H Hammond, Donald E Henson, Robert VP Hutter, Raymond B Nagle, et al · 2000
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Pathology and genetics of tumours of the digestive system
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An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (cin)
Stephen J Keenan, James Diamond, W Glenn McCluggage, Hoshang Bharucha, Deborah Thompson, Peter H Bartels, and Peter W Hamilton · 2000
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Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
Frederic Zana and J-C Klein · 2001
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The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia
James Diamond, Neil H Anderson, Peter H Bartels, Rodolfo Montironi, and Peter W Hamilton · 2004
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Augmented cell-graphs for automated cancer diagnosis
Cigdem Demir, S Humayun Gultekin, and Bulent Yener · 2005
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A new model for learning in graph domains
Marco Gori, Gabriele Monfardini, and Franco Scarselli · 2005
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Cell-graph mining for breast tissue modeling and classification
Cemal Cagatay Bilgin, Cigdem Gunduz Demir, Chandandeep Nagi, and Bulent Yener · 2007
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Neural network for graphs: A contextual constructive approach
Alessio Micheli · 2009
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The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini · 2009
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Ecm-aware cell-graph mining for bone tissue modeling and classification
Cemal Cagatay Bilgin, Peter Bullough, George E Plopper, and Bulent Yener · 2010
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Computerized classification of intraductal breast lesions using histopathological images
M Murat Dundar, Sunil Badve, Gokhan Bilgin, Vikas Raykar, Rohit Jain, Olcay Sertel, and Metin N Gurcan · 2011
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Prostate cancer grading: Gland segmentation and structural features
Kien Nguyen, Bikash Sabata, and Anil K Jain · 2012
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Follicular lymphoma grading using cell-graphs and multi-scale feature analysis
Basak Oztan, Hui Kong, Metin N Gürcan, and Bülent Yener · 2012
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Spectral networks and locally connected networks on graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann LeCun · 2014
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Learning convolutional neural networks for graphs
Mathias Niepert, Mohamed Ahmed, and Konstantin Kutzkov · 2016
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Breast cancer histopathological image classification using convolutional neural networks
High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection
Angel Cruz-Roa, Hannah Gilmore, Ajay Basavanhally, Michael Feldman, Shridar Ganesan, Natalie Shih, John Tomaszewski, Anant Madabhushi, and Fabio González · 2018
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Detection and classification of cancer in whole slide breast histopathology images using deep convolutional networks
Baris Gecer, Selim Aksoy, Ezgi Mercan, Linda G Shapiro, Donald L Weaver, and Joann G Elmore · 2018
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Classification of lung cancer histology images using patch-level summary statistics
Simon Graham, Muhammad Shaban, Talha Qaiser, Navid Alemi Koohbanani, Syed Ali Khurram, and Nasir Rajpoot · 2018
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Cellular community detection for tissue phenotyping in histology images
Sajid Javed, Muhammad Moazam Fraz, David Epstein, David Snead, and Nasir Rajpoot · 2018
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Deeper insights into graph convolutional networks for semi-supervised learning
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Fabio Alexandre Spanhol, Luiz S Oliveira, Caroline Petitjean, and Laurent Heutte · 2016
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Cell-graphs: image-driven modeling of structure-function relationship
Bulent Yener · 2016
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Classification of breast cancer histology images using convolutional neural networks
Teresa Araújo, Guilherme Aresta, Eduardo Castro, José Rouco, Paulo Aguiar, Catarina Eloy, António Polónia, and Aurélio Campilho · 2017
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Glandular morphometrics for objective grading of colorectal adenocarcinoma histology images
Ruqayya Awan, Korsuk Sirinukunwattana, David Epstein, Samuel Jefferyes, Uvais Qidwai, Zia Aftab, Imaad Mujeeb, David Snead, and Nasir Rajpoot · 2017
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Xception: Deep learning with depthwise separable convolutions
François Chollet · 2017
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Inductive representation learning on large graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Qimai Li, Zhichao Han, and Xiao-Ming Wu · 2018
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Improving Whole Slide Segmentation Through Visual Context - A Systematic Study
Korsuk Sirinukunwattana, Nasullah Khalid Alham, Clare Verrill, and Jens Rittscher · 2018
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Novel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer
Korsuk Sirinukunwattana, David Snead, David Epstein, Zia Aftab, Imaad Mujeeb, Yee Wah Tsang, Ian Cree, and Nasir Rajpoot · 2018
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Representation learning on graphs with jumping knowledge networks
Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, and Stefanie Jegelka · 2018
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Hierarchical graph representation learning with differentiable pooling
Zhitao Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, and Jure Leskovec · 2018
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An end-to-end deep learning architecture for graph classification
Muhan Zhang, Zhicheng Cui, Marion Neumann, and Yixin Chen · 2018
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Multi-label image recognition with graph convolutional networks
Zhaomin Chen, Xiushen Wei, Peng Wang, and Yanwen Guo · 2019
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Fast graph representation learning with PyTorch Geometric
Matthias Fey and Jan E. Lenssen · 2019
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Hongyang Gao and Shuiwang Ji · 2019
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MILD-Net: Minimal information loss dilated network for gland instance segmentation in colon histology images
Simon Graham, Hao Chen, Jevgenij Gamper, Qi Dou, Pheng-Ann Heng, David Snead, Yee Wah Tsang, and Nasir Rajpoot · 2019
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Hover-net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images
Simon Graham, Quoc Dang Vu, Shan E Ahmed Raza, Ayesha Azam, Yee Wah Tsang, Jin Tae Kwak, and Nasir Rajpoot · 2019
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Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images
Muhammad Shaban, Ruqayya Awan, Muhammad Moazam Fraz, Ayesha Azam, David Snead, and Nasir M. Rajpoot · 2019
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CIA-Net: Robust nuclei instance segmentation with contour-aware information aggregation
Yanning Zhou, Omer Fahri Onder, Qi Dou, Efstratios Tsougenis, Hao Chen, and Pheng-Ann Heng · 2019
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